评估ASD分类的动态时间扭曲函数连接性的预测能力。

IF 3.3 Q2 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Imaging Pub Date : 2023-10-25 eCollection Date: 2023-01-01 DOI:10.1155/2023/8512461
Christopher Liu, Juanjuan Fan, Barbara Bailey, Ralph-Axel Müller, Annika Linke
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引用次数: 0

摘要

功能连接MRI(fcMRI)是一种用于通过测量大脑不同区域的血氧水平依赖性(BOLD)信号之间的时间相关性来研究其功能连接性的技术。fcMRI通常使用Pearson相关性(PC)进行测量,该相关性假设时间序列之间没有滞后。动态时间扭曲(DTW)是一种衡量时间序列之间相似性的替代方法,对这种时滞具有鲁棒性。我们使用PC fcMRI数据和DTW fcMRI数据作为机器学习模型中的预测因素,对自闭症谱系障碍(ASD)进行分类。当与主成分分析等降维技术相结合时,用DTW估计的功能连接性比用PC估计的功能连通性显示出更大的预测能力。我们的结果表明,DTW-fcMRI可以是一种合适的替代测量方法,可以以不同但互补的方式来表征fcMRI,值得继续研究的PC fcMRI方法。在研究交叉验证(CV)的不同变体时,我们的结果表明,当需要调整模型超参数并同时评估模型性能时,嵌套在保留一个CV中的K折叠CV在性能和计算速度方面可能是一个有竞争力的竞争者,尤其是在样本量不大的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing Predictive Ability of Dynamic Time Warping Functional Connectivity for ASD Classification.

Functional connectivity MRI (fcMRI) is a technique used to study the functional connectedness of distinct regions of the brain by measuring the temporal correlation between their blood oxygen level-dependent (BOLD) signals. fcMRI is typically measured with the Pearson correlation (PC), which assumes that there is no lag between time series. Dynamic time warping (DTW) is an alternative measure of similarity between time series that is robust to such time lags. We used PC fcMRI data and DTW fcMRI data as predictors in machine learning models for classifying autism spectrum disorder (ASD). When combined with dimension reduction techniques, such as principal component analysis, functional connectivity estimated with DTW showed greater predictive ability than functional connectivity estimated with PC. Our results suggest that DTW fcMRI can be a suitable alternative measure that may be characterizing fcMRI in a different, but complementary, way to PC fcMRI that is worth continued investigation. In studying different variants of cross validation (CV), our results suggest that, when it is necessary to tune model hyperparameters and assess model performance at the same time, a K-fold CV nested within leave-one-out CV may be a competitive contender in terms of performance and computational speed, especially when sample size is not large.

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来源期刊
CiteScore
12.00
自引率
0.00%
发文量
11
审稿时长
20 weeks
期刊介绍: The International Journal of Biomedical Imaging is managed by a board of editors comprising internationally renowned active researchers. The journal is freely accessible online and also offered for purchase in print format. It employs a web-based review system to ensure swift turnaround times while maintaining high standards. In addition to regular issues, special issues are organized by guest editors. The subject areas covered include (but are not limited to): Digital radiography and tomosynthesis X-ray computed tomography (CT) Magnetic resonance imaging (MRI) Single photon emission computed tomography (SPECT) Positron emission tomography (PET) Ultrasound imaging Diffuse optical tomography, coherence, fluorescence, bioluminescence tomography, impedance tomography Neutron imaging for biomedical applications Magnetic and optical spectroscopy, and optical biopsy Optical, electron, scanning tunneling/atomic force microscopy Small animal imaging Functional, cellular, and molecular imaging Imaging assays for screening and molecular analysis Microarray image analysis and bioinformatics Emerging biomedical imaging techniques Imaging modality fusion Biomedical imaging instrumentation Biomedical image processing, pattern recognition, and analysis Biomedical image visualization, compression, transmission, and storage Imaging and modeling related to systems biology and systems biomedicine Applied mathematics, applied physics, and chemistry related to biomedical imaging Grid-enabling technology for biomedical imaging and informatics
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